1. Field of the Invention
This invention relates to diagnostic imaging in general, and to measurement of the mechanical properties of tissue in particular.
2. Description of the Related Art
The basis of medical imaging is the measurement of a property of tissue that varies with tissue composition. Medical images are formed by displaying intensities as a function of these properties measured at multiple locations in the body. From such images, a depiction of anatomy or pathology is gained. Each different imaging modality in common use, such as X-ray, computed tomography, ultrasound and magnetic resonance imaging, measures a different property of tissue.
Mechanical properties of tissue are important indicators of disease potential. Indeed, palpation techniques are commonly used by medical doctors to determine the potential for disease—for example, stiffer tissue regions that can be felt as harder objects can indicate the presence of breast or liver malignancies. There are a number of in-vivo techniques for measuring mechanical properties of tissue.
Static Elastography is a new medical imaging modality that aims to depict elasticity, a mechanical property of tissue. Elasticity is also referred to as stiffness, or the inverse compliance. The variation of elasticity among tissue types and pathology is well known. A number of journal articles describing the clinical applications of elastography are listed by Hall et al. in U.S. Pat. No. 6,508,768. In fact, elastography can be considered as an extension of the traditional diagnostic technique of palpation—the pressing of tissue to feel for differences in elasticity.
The history and development of elastography is given in the following reviews:
J. Ophir, S. K. Alam, B. Garra, F. Kallel, E. Konofagou, T. Krouskop and T. Varghese, “Elastography: ultrasonic estimation and imaging of the elastic properties of tissue”, J. Eng. Med., 213:203-233, 1999.
J. Ophir, I. Cespedes, H. Ponnekanti, and Y. Yazdi, “Elastography: ultrasonic imaging of tissue strain and elastic modulus in vivo”, Eur. J. Ultrasound, 3:49-70, 1996.
L. Gao, K. J. Parker, R. M. Lemer and S. F. Levinson, “Imaging of the elastic properties of tissue—a review”, Ultrason. Med. Biol., 22(8):959-977, 1996.
Depending on the technique of generating the measured tissue displacement, static elastography methods can be classified as employing global deformation or local deformation.
Measurement of applied global deformation. In static elastography, two images are taken of a region of tissue. One image is taken during compression of the tissue with a nominal static external force. The second image is taken during compression with a higher static external force. The difference between the images is used to calculate relative elasticity. The external force refers to axial pressure applied typically to the surface of the skin above a region of interest. The basic principle is that stiff tissues will compress less than compliant tissues. Dividing each image into small regions and comparing the movement of these regions between the two images provides a quantitative measurement of the local strain. Provided the stress induced from the external force is uniform throughout the tissue, then local elasticity estimates can be made. The underlying assumption is that the strain is linearly related to the stress and that this relationship is described mathematically by a linear scale factor called the Young's modulus, or simply elasticity. Ultrasound is a common imaging modality for this method because it is ubiquitous, non-invasive, safe, inexpensive and portable. Patents of this approach include those by Ophir et al., in U.S. Pat. Nos. 5,107,837, 5,178,147, 5,293,870, 5,474,070, Konofagou et al in U.S. Pat. No. 6,270,459, Alam et al. in U.S. Pat. No. 6,514,204, Steinberg et al. in U.S. Pat. No. 5,839,441, Hall et al. in U.S. Pat. No. 6,508,768, VonBehren et al. in U.S. Pat. No. 6,558,324 and Cohen-Bacrie et al. in U.S. Pat. No. 6,176,827. The differences among these patents are mainly in the construction of the apparatus, the methods to compute strain from the ultrasound data and the display of the results.
Measurement of local deformation in response to focused ultrasound excitation. The second category of static elastography describes methods that excite only a small volume of tissue interior to the body using high intensity focused ultrasonic waves. In Nightingale et al. in U.S. Pat. No. 6,371,912 the high intensity ultrasound produces an acoustic radiation force and is measured with a second set of low-intensity ultrasound images. The high intensity pushing pulses are interleaved with the low intensity imaging pulses to provide more rapid measurements. The relative local displacement is measured at different locations and displayed. The displacements are related to the local elasticity. Tissue dynamics are not captured in the process.
The major disadvantage of all static elastography methods is that they measure only static properties of tissue. In addition, because static elastography uses information at a single frequency (zero Hz or dc), the method is sensitive to noise and measurement bias.
In what we will call dynamic elastography, a force is applied to tissue and the resulting tissue motion is measured, i.e., multiple tissue displacement or velocity measurements are made over a period of time. These measurements can be displayed directly (e.g., measured magnitude of tissue velocity generated by a vibration source) or following some excitation-dependent signal processing (e.g., the quality factor of the tissue velocity frequency response to a vibration source acting at different frequencies).
There are many methods proposed for dynamic elastography. We will classify these broadly into the following four categories, based on whether tissue excitation and measurement is local, and whether there is an underlying tissue model whose parameters are being identified.
We will start by discussing three approaches that do not rely upon fitting the data to a parameterized tissue model.
Velocity response to an external vibration source. The first category of dynamic elastography describes methods that apply mechanical waves globally to a region of tissue using an external vibration source and then measure the resulting tissue motions. The tissue response is usually measured by ultrasound as described in Parker et al. in U.S. Pat. Nos. 5,086,775, 5,099,848, and Lin in U.S. Pat. Nos. 5,919,139, and 6,068,597. Ultrasound is normally used here because Doppler imaging is widely available on commercial ultrasound machines. The Doppler signals measure local velocity and the absence of velocity can indicate the presence of stiff inclusions such as tumors. As an alternative, magnetic resonance imaging offers improvements in image quality, at the expense of speed and cost. See for example, U.S. Pat. No. 6,486,669 described later.
In the methods disclosed in U.S. Pat. Nos. 5,086,775, 5,099,848, 5,919,139, and 6,068,597, the tissue is excited with a vibrator at audio frequencies and the tissue response is measured by power Doppler measurements. In U.S. Pat. Nos. 5,086,775 and 5,099,848, a mechanical exciter sweeps through a range of audio frequencies until a resonant frequency is detected. In U.S. Pat. No. 5,086,775 Doppler shifted signals are analyzed to find the vibration amplitude of a given region of interest. In U.S. Pat. No. 5,099,848, Doppler shifted signals are analyzed to find the vibration amplitude, the discrete eigenmodes, and eigenfrequency of the tissue. These measurements are then converted into other properties such as shear velocity and Q parameter—the quality factor—and displayed. In U.S. Pat. No. 5,919,139, the Doppler shifted signals are analyzed to find the tissue vibration amplitude, the frequency, and the variance. Various combinations of these properties are displayed. In U.S. Pat. No. 6,068,597, the tissue is vibrated with a wide range of frequencies to obtain the full frequency spectrum of the tissue at different locations. Various measurements of the shape of the spectrum around the resonance peak are then displayed.
In all four of these dynamic imaging patents, measurements are made of the velocity and resonance behavior of the tissue, but they are not based on modelling the underlying properties of the tissue, such as the elasticity, viscosity and density that produces the resonance behavior. Moreover, the measurements must be made with an excitation of only one frequency at a time, making the acquisition of data slow.
Tissue response from localized displacements. Sarvazyan in U.S. Pat. No. 5,606,971 uses high-intensity focused ultrasonic waves that are amplitude modulated to generate shear waves at a single location in the tissue. To obtain an image, localized excitations and measurements are repeated at different locations. The shear waves are detected by measuring their amplitude and phase on the surface of the tissue. At least one propagation parameter of the shear waves in the tissue is determined from the phase and amplitude measurements. The parameter can be one of the following group of parameters: shear wave velocity, shear wave attenuation coefficient, amplitude and velocity of shear displacement of tissue particles in the propagating shear wave, spatial an temporal dependencies of these amplitude and velocity of shear displacement of tissue particles. From these calculations, at least one mechanical parameter of tissue is derived, such as shear elasticity modulus, Young's modulus, dynamic shear viscosity, and mechanical impedance. The way the data is analyzed is local in the sense that the calculation of a tissue parameter at a single location is done without considering the effect of the properties of the neighboring tissue regions. This type of analysis is possible because the spatial decay of shear waves is rapid, so neighboring effects are neglected. The requirement that localized shear waves be used constitutes a significant drawback. Only one small region can be excited at a time and the excitation-measurement process must be repeated for multiple regions. This reduces the speed of forming a complete image. And again, the use of high intensity focused ultrasound poses a possible hazard to the patient.
Acoustic emissions from localized displacements. These dynamic elastography methods directly measure the acoustic emissions produced by tissue vibrating as a result of a localized oscillating radiation force. For a constant frequency radiation force, tissues with different viscoelastic properties will produce different emissions. The main idea is to create an oscillating point force in the tissue and measure the emission with a hydrophone. By raster scanning the point source across a region of interest, an image is formed from the magnitude or phase of the measured emissions. The oscillating point force is produced by the intersection of two focused continuous wave ultrasound beams at different frequencies. The interference of the beams at the focal point produces sinusoidal modulation of the ultrasound energy, effectively vibrating the tissue at that point. The use of such systems is called vibro-acoustography. See Greenleaf et al. in U.S. Pat. Nos. 5,903,516 and 5,991,239. The drawbacks of this approach include the need for specialized equipment for both producing the oscillating point force and measuring the emissions. It also does not measure the underlying properties of the tissue, only the resonance behavior. Moreover, it requires raster scanning of a region of interest, instead of allowing simultaneous measurements. This reduces the speed of forming a complete image.
Both localized methods—tissue response and acoustic emissions—produce images of one or more aspects of the tissue response to the dynamic excitations, but do not identify a specific model of the tissue dynamics. Alternatively, the tissue dynamics can be modelled using a parametric model, and the model parameters can be obtained from the measured responses to tissue excitation. The dynamic response of human tissue depends on both the amplitude and the frequency of the excitation (Y. C. Fung, “Biomechanics: Mechanical Properties of Living Tissues”, Springer, 1993). Nevertheless, if the amplitude of excitation is small, and frequencies are low, then a linear viscoelastic model can used as a reasonable approximation of the tissue dynamics. We now discuss two approaches that attempt to fit the data to a linear parameteric tissue model.
Parameter identification based on the wave equation and sinusoidal excitation. Sinkus et al. in U.S. Pat. No. 6,486,669 use a mechanical external excitation and magnetic resonance imaging to extract tissue properties from a linear viscoelastic model. This is therefore categorized as having global excitation with model parameter identification. A method is disclosed for vibrating the tissue to create longitudinal mechanical waves with periodic signals, preferably sinusoids, and to obtain the phase and amplitude of the single tone sinusoidal vibrations. To obtain both phase and amplitude, the images and the excitation must be carefully synchronized. From these measurements, they solve the wave equation for the viscoelastic model and calculate the model parameters of elasticity, Poison's ratio, tissue density and attenuation. In particular, the time independent solution of the partial differential wave equations is used. With a time independent approach, the tissue must be excited with a periodic signal, such as one or more toned sinusoids, and an equilibrium must be reached to eliminate the transient responses. Thus, this method is restricted to using excitations with periodic amplitudes to be able to reach equilibrium, and where the ratios of the frequencies is an integer.
The requirement that the excitation consist of carefully controlled frequencies and phases in synchronization with magnetic resonance imaging means that a very complicated system is needed compared to other techniques. Another limitation is the need to reach an equilibrium state before measurements can begin. Since tissue relaxation in response to an excitation may take seconds, the reported times required to obtain an image of parameters is of the order of 30 minutes (R. Sinkus, J. Lorenzen, D. Schrader, M. Lorenzen, M. Dargatz, and D. Holz, “High-resolution tensor MR elastography for breast tumour detection”, Phys. Med. Biol. 45, 2000).
Measurement and parameter fit to localized time response to focused ultrasound excitation. In a paper by F. Viola and W. Walker, “Imaging viscoelastic properties of the vitreous”, IEEE Ultrasonics Symposium, 2001, focused ultrasound is used to generate a step force in a localized region of tissue. This tissue region is displaced as a result, and its displacement as a function of time is used to identify the relative stiffness and relative viscosity with which this region is connected to neighboring tissue. This is therefore categorized as having local excitation with model parameter identification. While this method does measure dynamic properties of tissue (relative viscosity), it suffers from a number of drawbacks. First, while focused ultrasound can produce a step force in a small isolated region, this process must be repeated many times at many locations to form a complete image. The speed of the repeated measurements is limited by the need for the tissue to relax from the step force. Viola et al. do not describe a method to speed up the imaging of a larger region and such method is not obvious. Second, the identification technique Viola et al. use to compute relative stiffness and viscosity relies upon the step response of tissue. In essence, a fit to an exponentially decaying tissue region displacement must be obtained. It is well known to experts in parameter identification (see for example L. Ljung, “System Identification, Theory For The User”, Prentice Hall, 1999) that such an approach can fail in the presence of noise. Third, in order to obtain dynamic tissue parameters, Viola et al. fit the actual tissue region response to a model using nonlinear optimization techniques. Many iterations may be required for such an approach to produce a set of parameters. Furthermore, there may be local minima.
So in summary, the static elastography methods (both local and global excitation methods) are incapable of measuring the dynamic properties of tissue. The dynamic elastography methods with local excitation have shown an ability to measure some dynamic properties, but the local nature of excitation makes the imaging procedure slow. The current dynamic methods with global excitation are also slow because of the need to either synchronize with the imaging device after equilibrium, or sweep through a range of excitation frequencies. Those methods that excite only a single frequency can only characterize a subset of the dynamic properties, compared to methods that excite a range of frequencies. Moreover, no dynamic elastography method (including the dynamic methods with either local or global excitations) has so far proposed a method of excitation combining multiple frequency components together, so that robust system identification techniques can be employed to identify the tissue properties.